Evaluation of the IRI-2016 and NeQuick electron content specification by COSMIC GPS radio occultation,ground-based GPS and Jason-2 joint altimeter/GPS observations

We examined performance of two empirical profile-based ionospheric models, namely IRI-2016 and NeQuick-2, in electron content (EC) and total electron content (TEC) representation for different seasons and levels of solar activity. We derived and analyzed EC estimates in several representative altitudinal intervals for the ionosphere and the plasmasphere from the COSMIC GPS radio occultation, ground-based GPS and Jason-2 joint altimeter/GPS observations. It allows us to estimate a quantitative impact of the ionospheric electron density profiles formulation in several altitudinal intervals and to examine the source of the model-data discrepancies of the EC specification from the bottom-side ionosphere towards the GPS orbit altitudes. The most pronounced model-data differences were found at the low latitude region as related to the equatorial ionization anomaly appearance. Both the IRI-2016 and NeQuick-2 models tend to overestimate the daytime ionospheric EC and TEC at low latitudes during all seasons of low solar activity. On the contrary, during high solar activity the model results underestimated the EC/TEC observations at low latitudes. We found that both models underestimated the EC for the topside ionosphere and plasmasphere regions for all levels of solar activity. For low solar activity, the underestimated EC from the topside ionosphere and plasmasphere can compensate the overestimation of the ionospheric EC and, consequently, can slightly decrease the resulted model overestimation of the ground-based TEC. For high solar activity, the underestimated EC from the topside ionosphere and plasmasphere leads to a strengthening of the model underestimation of the ground-based TEC values. We demonstrated that the major source of the model-data discrepancies in the EC/TEC domain comes from the topside ionosphere/plasmasphere system.     

Comparison of subpeak electron density profiles deduced from ionograms with the International Reference Ionosphere (IRI)

A comparison is made between the subpeak electron density profiles, obtained at selected local hours by vertical ionospheric sounding at the ionospheric station at Sofia (42.6°N; 23.3°E) and the IRI profiles for spring, summer, winter and two levels of solar activity (R = 10 and 100). It is demonstrated that the ionospheric profiles above Sofia are in rather good agreement with the values computed with IRI.     

Comparison of different N(h) profiles with mid-latitude ionospheric observations

After inversion, N(h) profiles obtained from ionograms that had been recorded during high solar activity at two mid-latitutde stations have been compared with those derived from IRI90 and DGR ionospheric models. A small data set has been selected such that both geomagnetically quiet and disturbed conditions are represented.     

Solar activity variations of ionosonde measurements and modeling results

The time series of hourly electron density profiles N(h) obtained at several mid-latitude stations in Europe have been used to obtain N(h) profiles on a monthly basis and to extract both the expected bottomside parameters and a proxy of the ionospheric variability as functions of time and height. With these data we present advances on a “Local Model” technique for the parameters B0 and B1, its applicability to other ionospheric stations, to other bottomside ionospheric parameters, and to modeling the time/height variability of the profile. The Local Model (LM) is an empirical model based on the experimental results of the solar activity dependence of the daily and seasonal behavior of the above parameters. The LM improves the IRI-2001 prediction of the B0 and B1 by factor of two at mid-latitudes. Moreover, the LM can be used to simulate other ionospheric parameters and to build mean N(h) profiles and the deviations from them. The modeling of both the average N(h) profiles and their deviations is an useful tool for ionospheric model users who want to know both the expected patterns and their deviations.     

Observed and model N(h) profiles for the Bulgarian region

In this paper, combined bottom- and topside ionospheric N(h)-profiles are presented for the Bulgarian region. The profiles were constructed using ground (ionospheric observatories Sofia and Michurin) and satellite (Interkosmos-19) observations /1/.The observatories make quarter-hourly observations; in order to connect bottom and upper parts of the N(h) profile, we selected satellite orbits passing rather near to the observatory (zenith distance lsss than 100 km). Thus the time difference between ground station and satellite measurement was never more than 7.5 min.     

Modelling the plasmasphere for the international reference ionosphere

The paper discusses how profiles of electron and/or ion distributions that are produced by two different computer models can be smoothly coupled together. The first of these models is the empirical International Reference Ionosphere which produces a vertical profile of ionospheric parameters up to an altitude of 1000 km. The second is a physically-based, diffusive equilibrium model of the plasmasphere based upon the theoretical work of Angerami and Thomas /1/, in which plasma is constrained to move parallel to the Earth's magnetic field lines. Some problems associated with this work are considered, as are some initial results.     

Accuracy of IRI profiles of ionospheric density and temperatures derived from comparisons to Kharkov incoherent scatter radar measurements

The incoherent scatter radar (ISR) facility in Kharkov, Ukraine (49.6°N, 36.3°E) measures vertical profiles of electron density, electron and ion temperature, and ion composition of the ionospheric plasma up to 1100 km altitude. Acquired measurements constitute an accurate ionospheric reference dataset for validation of the variety of models and alternative measurement techniques. We describe preliminary results of comparing the Kharkov ISR profiles to the international reference ionosphere (IRI), an empirical model recognized for its reliable representation of the monthly-median climatology of the density and temperature profiles during quiet-time conditions, with certain extensions to the storm times. We limited our comparison to only quiet geomagnetic conditions during the autumnal equinoxes of 2007 and 2008. Overall, we observe good qualitative agreement between model and data both in time and with altitude. Magnitude-wise, the measured and modeled electron density and plasma temperatures profiles appear different. We discovered that representation accuracy improves significantly when IRI is driven by observed-averaged values of the solar activity index rather than their predictions. This result motivated us to study IRI performance throughout protracted solar minimum of the 24th cycle. The paper summarizes our observations and recommendations for optimal use of the IRI.     

不同上边界条件下的极区电离层数值模拟

利用一维自洽的极区电离层模型,研究了沿磁力线方向不同电离层-磁层耦合条件下极区电离层的响应.此模型在110-610km的电离层空间区域内,综合求解描述极区电离层的连续性方程、动量方程和能量方程,以得到电离层数值解.研究发现,上边界条件在200 km以上的高度能显著地影响电离层参量的形态.较高的O+上行速度对应较低的F层峰值和较高的电子温度.不同边界O+上行速度对应的温度高度剖面完全不同.200km以上电子温度高度剖面不但由来自磁层的热流通量所控制,同时还受到场向O+速度的影响.对利用电离层模型研究电离层内部物理过程提出了建议.      

The occurrence of the mid-latitude ionospheric trough in GPS-TEC measurements

Simultaneous GPS observations from about 150 stations of European Permanent Network (EPN) have been used for studying dynamics of latitudinal profiles and structure of mid-latitude ionospheric trough (MIT). For the analyses, the TEC maps over Europe were created with high spatial and temporal resolution. The latitudinal profiles were produced from TEC maps with one-hour interval for geographic latitude range from 35N to 75N. The structure of latitudinal profiles relates to the occurrence of the ionospheric trough. The location of the trough depends on season, local time, and both geophysical and geomagnetic conditions. The trough structure in GPS-TEC demonstrates a smooth shape. The trough occurrence as a distinguished structure is more distinct during winter. The relation of TEC in the trough minimum to the equator and polar walls amounted to a factor of 2–4.     

A new inversion algorithm for HF sky-wave backscatter ionograms

HF sky-wave backscatter sounding system is capable of measuring the large-scale, two-dimensional (2-D) distributions of ionospheric electron density. The leading edge (LE) of a backscatter ionogram (BSI) is widely used for ionospheric inversion since it is hardly affected by any factors other than ionospheric electron density. Traditional BSI inversion methods have failed to distinguish LEs associated with different ionospheric layers, and simply utilize the minimum group path of each operating frequency, which generally corresponds to the LE associated with the F₂ layer. Consequently, while the inversion results can provide accurate profiles of the F region below the F₂ peak, the diagnostics may not be so effective for other ionospheric layers. In order to resolve this issue, we present a new BSI inversion method using LEs associated with different layers, which can further improve the accuracy of electron density distribution, especially the profile of the ionospheric layers below the F₂ region. The efficiency of the algorithm is evaluated by computing the mean and the standard deviation of the differences between inverted parameter values and true values obtained from both vertical and oblique incidence sounding. Test results clearly manifest that the method we have developed outputs more accurate electron density profiles due to improvements to acquire the profiles of the layers below the F₂ region. Our study can further improve the current BSI inversion methods on the reconstruction of 2-D electron density distribution in a vertical plane aligned with the direction of sounding.     

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.     

Ionospheric path delay models for spaceborne GPS receivers flying in formation with large baselines

GPS relative navigation filters could benefit notably from an accurate modeling of the ionospheric delays, especially over large baselines (>100 km) where double difference delays can be higher than several carrier wavelengths. This paper analyzes the capability of ionospheric path delay models proposed for spaceborne GPS receivers in predicting both zero-difference and double difference ionospheric delays. We specifically refer to relatively simple ionospheric models, which are suitable for real-time filtering schemes. Specifically, two ionospheric delay models are evaluated, one assuming an isotropic electron density and the other considering the effect on the electron density of the Sun aspect angle. The prediction capability of these models is investigated by comparing predicted ionospheric delays with measured ones on real flight data from the Gravity Recovery and Climate Experiment mission, in which two satellites fly separated of more than 200 km. Results demonstrate that both models exhibit a correlation in the excess of 80% between predicted and measured double-difference ionospheric delays. Despite its higher simplicity, the isotropic model performs better than the model including the Sun effect, being able to predict double differenced delays with accuracy smaller than the carrier wavelength in most cases. The model is thus fit for supporting integer ambiguity fixing in real-time filters for relative navigation over large baselines. Concerning zero-difference ionospheric delays, results demonstrate that delays predicted by the isotropic model are highly correlated (around 90%) with those estimated using GPS measurements. However, the difference between predicted and measured delays has a root mean square error in the excess of 30 cm. Thus, the zero-difference ionospheric delays model is not likely to be an alternative to methods exploiting carrier-phase observables for cancelling out the ionosphere contribution in single-frequency absolute navigation filters.     

Refinement of global ionospheric coefficients for GNSS applications: Methodology and results

We developed the methodology for the optimal estimation of global ionospheric coefficients of the current Global Navigation Satellite Systems (GNSSs), including the eight- and ten-parameter Klobuchar-like as well as NeQuick models. The ionospheric coefficients of those correction models are calculated from two sets of globally distributed tracking stations of the International GNSS Services (IGS). Performance of the re-estimated Klobuchar-like and NeQuick coefficients are validated during 2002–2014 over the continental and oceanic areas, respectively. Over the continental areas, GPS TECs derived from 40 ground GPS receivers are selected as reference. The eight-, ten-parameter Klobuchar-like and NeQuick models can mitigate the ionospheric delay by 65.8, 67.3 and 75.0%, respectively. Over the global oceans, the independent TECs derived from Jason-1&2 altimeters are used as reference. The re-estimated ionospheric correction models can mitigate 56.1–66.7% of the delay errors. Compared to the original GPS Ionospheric Correction Algorithm (ICA), performance of those eight-, ten-parameter Klobuchar-like and NeQuick models has improved 3.4, 5.9 and 13.4% during the whole test period, respectively. The methodology developed here takes the advantage of high-quality ionospheric TECs derived from the global network of GNSS receivers. The re-estimated ionospheric coefficients can be used as precise ionospheric products to monitor and assess GNSS broadcast ionospheric parameters and to improve the performance of various single-frequency GNSS applications.     

Testing the three-dimensional IRI-SIRMUP-P mapping of the ionosphere for disturbed periods

This paper describes the three-dimensional (3-D) electron density mapping of the ionosphere given as output by the assimilative IRI-SIRMUP-P (ISP) model for three different geomagnetic storms. Results of the 3-D model are shown by comparing the electron density profiles given by the model with the ones measured at two testing ionospheric stations: Roquetes (40.8°N, 0.5°E), Spain, and San Vito (40.6°N, 17.8°E), Italy. The reference ionospheric stations from which the autoscaled foF2 and M(3000)F2 data as well as the real-time vertical electron density profiles are assimilated by the ISP model are those of El Arenosillo (37.1°N, 353.3°E), Spain, Rome (41.8°N, 12.5°E), and Gibilmanna (37.9°N, 14.0°E), Italy. Overall, the representation of the ionosphere made by the ISP model is better than the climatological representation made by only the IRI-URSI and the IRI-CCIR models. However, there are few cases for which the assimilation of the autoscaled data from the reference stations causes either a strong underestimation or a strong overestimation of the real conditions of the ionosphere, which is in these cases better represented by only the IRI-URSI model. This ISP misrepresentation is mainly due to the fact that the reference ionospheric stations covering the region mapped by the model turn out to be few, especially for disturbed periods when the ionosphere is very variable both in time and in space and hence a larger number of stations would be required. The inclusion of new additional reference ionospheric stations could surely smooth out this concern.     

A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network

There are remarkable ionospheric discrepancies between space-borne (COSMIC) measurements and ground-based (ionosonde) observations, the discrepancies could decrease the accuracies of the ionospheric model developed by multi-source data seriously. To reduce the discrepancies between two observational systems, the peak frequency (foF2) and peak height (hmF2) derived from the COSMIC and ionosonde data are used to develop the ionospheric models by an artificial neural network (ANN) method, respectively. The averaged root-mean-square errors (RMSEs) of COSPF (COSMIC peak frequency model), COSPH (COSMIC peak height model), IONOPF (Ionosonde peak frequency model) and IONOPH (Ionosonde peak height model) are 0.58 MHz, 19.59 km, 0.92 MHz and 23.40 km, respectively. The results indicate that the discrepancies between these models are dependent on universal time, geographic latitude and seasons. The peak frequencies measured by COSMIC are generally larger than ionosonde’s observations in the nighttime or middle-latitudes with the amplitude of lower than 25%, while the averaged peak height derived from COSMIC is smaller than ionosonde’s data in the polar regions. The differences between ANN-based maps and references show that the discrepancies between two ionospheric detecting techniques are proportional to the intensity of solar radiation. Besides, a new method based on the ANN technique is proposed to reduce the discrepancies for improving ionospheric models developed by multiple measurements, the results indicate that the RMSEs of ANN models optimized by the method are 14–25% lower than the models without the application of the method. Furthermore, the ionospheric model built by the multiple measurements with the application of the method is more powerful in capturing the ionospheric dynamic physics features, such as equatorial ionization, Weddell Sea, mid-latitude summer nighttime and winter anomalies. In conclusion, the new method is significant in improving the accuracy and physical characteristics of an ionospheric model based on multi-source observations.     

Mitigation of receiver biases in ionospheric observables from PPP with ambiguity resolution

PPP (Precise Point Positioning) is a GNSS (Global Navigation Satellite Systems) positioning method that requires SSR (State Space Representation) corrections in order to provide solutions with an accuracy of centimetric level. The so-called RT-PPP (Real-time PPP) is possible thanks to real-time precise SSR products, for orbits and clocks, provided by IGS (International GNSS Service) and its associate analysis centers such as CNES (Centre National d'Etudes Spatiales). CNES SSR products also enable RT-PPP with integer ambiguity resolution. In GNSS related literature, PPP with ambiguity resolution (PPP-AR) in real-time is often referred as PPP-RTK (PPP – Real Time Kinematic). PPP-WIZARD (PPP - With Integer and Zero-difference Ambiguity Resolution Demonstrator) is a software that is made available by CNES. This software is capable of performing PPP-RTK. It estimates slant ionospheric delays and other GNSS positioning parameters. Since ionospheric effects are spatially correlated by GNSS data from active networks, it is possible to model and provide ionospheric delays for any position in the network coverage area. The prior knowledge ionospheric delays can reduce positioning convergence for PPP-RTK users. Real-time ionospheric models could benefit from highly precise ionospheric delays estimated in PPP-AR. In this study, we demonstrate that ionospheric delays obtained throughout PPP-AR estimation are actu ally ionospheric observables. Ionospheric observables are biased by an order of few meters caused by the receiver hardware biases. These biases prohibit the use of PPP-WIZARD ionospheric delays to produce ionospheric models. Receiver biases correction is essential to provide ionospheric delays while using PPP-AR based ionospheric observables. In this contribution, a method was implemented to estimate and mitigate receiver hardware biases influence on slant ionospheric observables from PPP-AR. In order to assess the proposed approach, PPP-AR data from 12 GNSS stations were processed over a two-month period (March and April 2018). A comparison between IGS ionospheric products and PPP-AR based ionospheric observables corrected for receiver biases, resulted in a mean of differences of −39 cm and 51 cm standard deviation. The results are consistent with the accuracy of the IGS ionospheric products, 2–8 TECU, considering that 1 TECU is ~16 cm in L1. In another analysis, a comparison of ionospheric delays from 5 pairs of short baselines GNSS stations found an agreement of 0.001 m in mean differences with 22 cm standard deviation after receiver biases were corrected. Therefore, the proposed solution is promising and could produce high quality (1–2 TECU) slant ionospheric delays. This product can be used in a large variety of modeling approaches, since ionospheric delays after correction are unbiased. These results indicate that the proposed strategy is promising, and could benefit applications that require accuracy of 1–2 TECU (~16–32 cm in L1).     

Ionospheric F-region response to geomagnetic disturbances

The F2-region reaction to geomagnetic storms usually called as an ionospheric storm is a rather complicated event. It consists of so called positive and negative phases, which have very complicated spatial and temporal behavior. The main morphological features of ionospheric storms and the main processes governing their behavior were understood at the end of the 1900s and described in a series of review papers. During the recent decade there were many publications dedicated to the problem of ionospheric storms. In this paper a concept of ionospheric storm morphology and physics formulated at the end of the 1990s is briefly summarized and the most interesting results obtained in the 2000s are described. It is shown that the main features of the studies of the previous decade were: the use of GPS TEC data for analyzing the ionospheric storm morphology, attraction of sophisticated theoretical models for studying the processes governing ionospheric behavior in disturbed conditions, and accent to analysis of ionospheric behavior during prominent events (very strong and great geomagnetic storms). Also a special attention was paid to the pre-storm enhancements in foF2 and TEC.     

Ionospheric differential error determination using ray tracing for a short baseline

Since the United States government discontinued Selective Availability (SA) on 1 May 2000, ionospheric effects have been responsible for the largest errors in GPS systems. The standard Differential GPS (DGPS) method is incapable of completely eliminating the ionospheric error. This paper describes a new approach to determine the differential ionospheric error between geographically distributed receiver stations. The ray paths of GPS signals were simulated using a modified Jones 3D ray tracing programme that includes the effect of the geomagnetic field. A Nelder–Mead optimisation algorithm was embedded in the program to precisely determine the satellite-to-station path. A realistic ionospheric model is essential for accurate ray tracing results and for estimates of differential error that are accurate on sub-centimetre scales. Here, the ionospheric model used in the ray tracing programme was developed by fitting realistic ionosphere profiles with a number of exponential functions. Results were compared to the theoretical approach. Results show that the differential delay is about 1–5 cm at low elevation angles for a short baseline of 10 km, as reported in other literature. This delay is often neglected in DGPS application. The differential delay also shows a pattern similar to that predicted by the Klobuchar model. The method proposed here can be used to improve future GPS applications.     

Comparison of standard TEC models with a Neural Network based TEC model using multistation GPS TEC around the northern crest of Equatorial Ionization Anomaly in the Indian longitude sector during the low and moderate solar activity levels of the 24th solar cycle

The highest Total Electron Content (TEC) values in the world normally occur at Equatorial Ionization Anomaly (EIA) region resulting in largest ionospheric range delay values observed for any potential Space Based Augmentation System (SBAS). Reliable forecasting of TEC is crucial for satellite based navigation systems. The day to day variability of the location of the anomaly peak and its intensity is very large. This imposes severe limitations on the applicability of commonly used ionospheric models to the low latitude regions. It is necessary to generate a mathematical ionospheric forecasting and mapping model for TEC based on physical ionospheric influencing parameters. A model, IRPE-TEC, has been developed based on real time low latitude total electron content data using GPS measurements from a number of stations situated around the northern crest of the EIA during 2007 through 2011 to predict the vertical TEC values during the low and moderate solar activity levels of the 24th solar cycle. This model is compared with standard ionospheric models like International Reference Ionosphere (IRI) and Parameterized Ionospheric Model (PIM) to establish its applicability in the equatorial region for accurate predictions.